The MIL-based scheme has also been exploited in WS-TALs with point supervision [1]}, where the aforementioned issue still exists.
Our C\(^3\) N is generic and is expected to work well for this task. We take SFNet [1]} and LACP [3]} as the baselines, and conduct experiments on THUMOS14, BEOID [4]} and GTEA [5]}. As shown in Table REF  and Table REF , our C\(^3\) BN strategy improves the mAP of the SF-Net and LACP by a large margin. Besides, our method also outperforms recent proposed DC [6]}, and achieves SOTA performance on all three datasets.
These validate that our C\(^3\) BN is compatible with WS-TAL with different weak supervisions.
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